Hospital Implementation of Medical AI: Legal and Ethical Issues
2025-04-15 15:00 - 16:00 (America/New_York)
This talk will discuss legal and ethical issues that arise when hospitals implement medical AI, including discussing ambient listening, AI scribing, and AI drafting of communication with patients, as well as more clinical technologies.
ZOOM ID: 817 5305 8557
Bio:
Professor Cohen is a leading expert in bioethics, health law, and civil procedure. An elected member of the National Academy of Medicine, he has advised U.S. Vice President Harris on reproductive rights, discussed medical AI policy with the Korean Congress, and lectured globally. His work appears in top legal, medical, and public health journals, as well as major media outlets. A Harvard Law professor since 2008, he has authored over 200 articles and 20 books on topics like AI in medicine, reproductive technologies, and health policy. He also leads major research initiatives, provides expert testimony, and remains active in litigation and bioethics advisory roles.
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Prof. Cohen is one of the world’s leading experts on the intersection of bioethics (sometimes also called “medical ethics”) and the law, as well as health law. He also teaches civil procedure. He is an elected member of the National Academy of Medicine and has advised the U.S. Vice President Harris on reproductive rights, discussed medical AI policy with members of the Korean Congress, and lectured to legal, medical, and industry conferences around the world. His work has been frequently covered by or appeared in media venues such as PBS, NPR, ABC, NBC, CBS, CNN, the New York Times, The Washington Post, the Boston Globe.
He was the youngest professor on the faculty at Harvard Law School (tenured or untenured) both when he joined the faculty in 2008 (at age 29) and when he was tenured as a full professor in 2013 (at age 34), though not the youngest in history.
Prof. Cohen’s current projects relate to medical AI, mobile health and other health information technologies, abortion, reproduction/reproductive technology, the therapeutic use of psychedelic drugs, research ethics, organ transplantation, rationing in law and medicine, health policy, FDA law, translational medicine, medical tourism and many other topics.
He is the author of more than 200 articles and chapters and his award-winning work has appeared in leading legal (including the Stanford, Cornell, and Southern California Law Reviews), medical (including the New England Journal of Medicine, JAMA), bioethics (including the American Journal of Bioethics, the Hastings Center Report), scientific (Science, Cell, Nature Reviews Genetics) and public health (the American Journal of Public Health) journals, as well as Op-Eds in the New York Times, Washington Post, New Republic, Time Magazine, and other venues.
Cohen is the author, co-author, editor, or co-editor of more than 20 books. They include: COVID-19 and the Law (Cambridge University Press, 2023); Reproductive Technologies and the Law (Caroline Academic Press, 2022);The Future of Medical Device Regulation (Cambridge University Press, 2022) Consumer Genetic Technologies: Ethical and Legal Considerations (Cambridge University Press, 2021); Readings in Comparative Health Law and Bioethics (Carolina Academic Press, 2020); Disability, Health, Law, and Bioethics (Cambridge University Press, 2020); Transparency in Health and Health Care in the United States (Cambridge University Press, 2019); Health Care Law and Ethics (Aspen, 2018); Big Data, Health Law, and Bioethics (Cambridge University Press, 2018); Law, Religion, and Health in the United States (Cambridge University Press, 2017); Specimen Science (MIT Press, 2017); Nudging Health: Health Law and Behavioral Economics (John Hopkins University Press, 2016) The Oxford Handbook of U.S. Health Care Law (Oxford University Press, 2016); FDA in the Twenty-First Century: The Challenges of Regulating Drugs and New Technologies (Columbia University Press, 2015); Patients with Passports: Medical Tourism, Law, and Ethics (Oxford University Press, 2014); Human Subjects Research Regulation: Perspectives on the Future (MIT Press, 2014); The Globalization of Health Care: Legal and Ethical Issues (Oxford University Press, 2013).
For his law school teaching he was awarded the HLS Student Government Teaching and Advising Award in 2017. For the public he created the free online Harvard X class Bioethics: The Law, Medicine, and Ethics of Reproductive Technologies and Genetics, taken by more than 100,000 students. You can also watch his Tedx talk, Are There Non-Human Persons? Are There Non-Person Humans? He is also the faculty lead on Zero-L, an online course to help law students transition to law school that has been used by more than half of all U.S. law schools.
Prior to becoming a professor he served as a law clerk to Judge Michael Boudin of the U.S. Court of Appeals for the First Circuit and as a lawyer for U.S. Department of Justice, Civil Division, Appellate Staff, where he handled litigation in the Courts of Appeals and (in conjunction with the Solicitor General’s Office) in the U.S. Supreme Court. In his spare time (where he can find any!) he still litigates, having authored an amicus brief in the U.S. Supreme Court for in AMP v. Myriad, concerning whether human genes are patent eligible subject matter, a brief that was extensively discussed by the Justices at oral argument. Most recently he has helped with amicus briefs regarding mifepristone (for medical abortion) and gender-affirming care for trans minors. He also provides expert testimony in health law and bioethics litigation.
Cohen was selected as a Radcliffe Institute Fellow for the 2012-2013 year and by the Greenwall Foundation to receive a Faculty Scholar Award in Bioethics. He is also a Fellow at the Hastings Center, the leading bioethics think tank in the United States as well as being a fellow of the Pierre Elliot Trudeau Foundation. He leads the Project on Precision Medicine, Artificial Intelligence, and the Law (PMAIL), which is part of the larger Centre for Advanced Studies in Biomedical Innovation Law (CeBIL). He is also the principal investigator for Diagnosing in the Home: The Ethical, Legal, and Regulatory Challenges and Opportunities of Digital Home Health and the Project on Psychedelics Law and Regulation (POPLAR). He previously served as the co-lead on the Regulatory Foundations, Ethics, and Law Program of Harvard Catalyst and as one of the key co-investigators on the multi-million dollar Football Players Health Study at Harvard, focused on improving the health of NFL players.
Cohen is also one of three editors-in-chief of the Journal of Law and the Biosciences, a peer-reviewed journal published by Oxford University Press and serves on the editorial board for the American Journal of Bioethics. He served on the Steering Committee for Ethics for the Canadian Institutes of Health Research (CIHR), the Canadian counterpart to the NIH, and the Ethics Committee for the American College of Obstetricians and Gynecologists (ACOG) and the Ethics Committee of the U.S. Organ Procurement and Transplantation Network (OPTN). He has also served on the bioethics advisory groups for life sciences companies like Otsuka, Illumina, and Bayer.
You can freely download his work here, and follow him on twitter @CohenProf.

Voice Symposium & Hackathon 2025
2025-04-22 - 2025-04-24
REGISTRATION IS OPEN FOR THE 2025 VOICE AI SYMPOSIUM + HACKATHON
SUBMIT ABSTRACTS BY DECEMBER 15TH
DISCOUNTED REGISTRATION FOR B2AI MEMBERS (see below for details)

We’re excited to invite you to the 2025 Voice AI Symposium and Hackathon, presented by the NIH Common Fund’s Bridge2AI-Voice consortium! From April 22-24 in Tampa, this unique three-day event will bring together researchers, patients, clinician-scientists and top minds in artificial intelligence, bioethics, voice biomarkers, and transformative healthcare for an innovative and interactive hands-on experience.
2025 Voice AI Symposium + Hackathon
When: April 22-23 (Symposium) + Apri 24 (Hackathon)
Where: Sunny Tampa Florida! At the J.W. Marriott and the Morsani College of Medicine, Taneja College of Pharmacy and Heart Institute, Water Street
HIGHLIGHTS FROM LAST YEAR
Why Attend?
Our theme this year, “Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare”, will spotlight the real-world applications and ethical considerations of voice AI in healthcare. The symposium will feature prominent industry leaders and renowned bioethics experts, providing a valuable platform for interdisciplinary discussion and learning. Last year, we welcomed speakers from Google, Microsoft, Canary Speech, Sonde Health, Redenlab, NIH, and numerous international startups.
Highlights of the Symposium:

Interactive Panel Discussions: Engage with leaders and experts on the future of voice AI in healthcare, including ethical considerations and practical applications.

Deep Dive Workshops: Hands-on sessions designed to deepen your understanding and skill set in AI and voice biomarkers.

Tech Fair: A showcase of the latest tools and innovations in the field, allowing you to explore cutting-edge technologies up close.

Hackathon: A full day dedicated to solving real-world healthcare challenges alongside other participants, fostering collaboration and innovation.

Poster Competition: A fantastic opportunity for researchers to present their work, share insights, and receive valuable feedback from peers and experts.

Networking Event: Connect with professionals across academia, industry, healthcare, and patient advocacy. This is your chance to build valuable connections and explore collaborative opportunities.

Secure your place today and join us in Tampa for an unforgettable experience at the forefront of AI and healthcare.
B2AI members receive $100 off the cost of registration with the following code: B2AIdiscount!
Register Now: https://www.eventsquid.com/register/26215
Submit Abstracts: https://www.eventsquid.com/register/26217
We look forward to seeing you in April!
Warm regards,
Jamie Toghranegar

Jamie Toghranegar, SLPD, CCC-SLP, CBIS
Research Project Manager, Bridge2AI Voice
Speech Language Pathologist
USF Health Morsani College of Medicine
University of South Florida
12901 Bruce B. Downs Blvd.
Tampa, FL 33612

CM4AI Graph Community Detection Challenge
2025-05-14 - 2025-07-31
The Opportunity and A Call to Action
We are excited to announce the launch of the CM4AI Graph Community Detection competition on Kaggle! Participating in this challenge will give you a unique opportunity to be part of groundbreaking advancements in biomedical research as part of the Cell Maps for AI (CM4AI) initiative.
Challenge Dates: May 14, 2025 – July 31, 2025
Join the Frontier of Biomedical AI Research!
The Bridge2AI Functional Genomics Grand Challenge (Cell Maps for AI/CM4AI) is pleased to announce our Kaggle competition focused on using the data and tools generated by CM4AI and leveraging emerging AI/ML methods, such as graph and quantum machine learning, to advance biomedical science and precision medicine.
Competition Overview
The goal of this competition is to develop methods that identify communities within biological networks to uncover hidden structures and provide new insights into biological systems. By participating, you will help push the boundaries of AI/ ML applications in the life sciences.
Why Participate?

Shape the Future of Science: Successful approaches can redefine how we understand cellular systems, paving the way for innovative therapeutic strategies for cancer and other human disease.
Challenge Yourself: Engage in solving a cutting-edge problem that bridges the gap between AI/ML and molecular biology.
Be Part of a Global Community: Collaborate and compete with experts, researchers, and enthusiasts from diverse fields with mentorship from CM4AI investigators.

Key Details

CM4AI Resources: https://cm4ai.org and https://youtube.com/@CM4AI
Competition Link: https://www.kaggle.com/t/b25c9b18a199411892011bfb88680cf3
Objective: Detect and identify communities from CM4AI SEC-MS data, contributing to the Cell Maps for AI initiative.

Who Should Join?
This competition is open to anyone passionate about artificial intelligence/machine learning, computational biology, or biomedical research. Whether you’re a seasoned expert or an enthusiastic beginner, your contributions can help drive the next wave of discoveries.
Don’t miss this opportunity to be part of a transformative journey at the intersection of AI and molecular biology!

Join the Challenge Now

Spring 2025 All Hands & Open House Meeting
2025-05-20 - 2025-05-22 | NIH Neuroscience Center, 6001 Executive Blvd, Rockville, MD, 20852, United States
All Hands Conference
Our May 2025 All Hands Conference will be an opportunity for researchers and experts to engage in vibrant discussions. The NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2Al) program will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (Al) that tackles complex biomedical challenges beyond human intuition. The biomedical research community generates a wealth of data, but most of these data are not suitable for machine learning because they are incomplete. By bringing technological and biomedical experts together with social scientists and humanists, the Bridge2Al program will help bring solutions to this deficit.
Open House
The Bridge2Al Open House will focus on collaborative approaches, learn about current considerations, explore new datasets, and discuss other key issues related to bridging the gap from biomedical information to Al. Sessions will be centered around the activities of the Bridge2Al Data Generation Projects, which stemmed from Grand Challenges put forth by the National Institutes of Health (NIH).
📋 Check out Digital Program

Bridge2AI Spring 2025 Open House
2025-05-22 | NIH Neuroscience Center 6001 Executive Blvd Rockville MD United States
Join us for the second annual Bridge2AI Open House on Thursday, May 22, 2025, in Rockville, MD! This event provides an amazing opportunity for scientists, ethicists, coders, community members, and practitioners with diverse expertise and experience levels to come together to build unique solutions that will help solve a range of relevant problems. The Bridge2AI Open House will focus on key issues related to bridging the gap from biomedical information to AI. Sessions will be centered around the activities of the Bridge2AI Data Generation Projects, which stem from the National Institutes of Health’s (NIH) Grand Challenges.
Register By: May 16, 2025
Register Here

B2AI Discussion Forum on Emerging ELSI Issues: “Ethical, Legal, and Social Implications in AI Quality Assurance and Model Validation: Case Studies and Evolving Approaches” by Shannon McWeeney, Ph.D.
2025-06-17 15:00 - 16:00 (America/New_York)

MICCAI 2025 Multi Camera Robust Diagnosis of Fundus Diseases(MuCaRD) Challenge
2025-06-30 - 2025-10-10
Introduction
Fundus imaging is an indispensable tool in primary care for the early detection of major ophthalmic diseases—such as diabetic retinopathy and glaucoma—and for guiding treatment decisions. By noninvasively visualizing the retinal vasculature and subtle changes at the optic nerve head, fundus exams also serve as indicators of systemic health, making them a first line of patient management. With the widespread adoption of high-resolution, digital camera–based fundus imaging, a variety of imaging modalities have rapidly entered clinical practice. Recently, deep-learning–based models for classifying fundus diseases have demonstrated high sensitivity and specificity and have proven their clinical utility by being integrated into numerous software medical devices (SaMD). For example, automated diabetic retinopathy screening systems and glaucoma-progression monitoring tools are already commercially available, contributing broadly to diagnostic support and patient screening. However, most models are trained and validated on data from a single camera type, which limits their performance when applied to images from new or infrequently used devices. To overcome these practical constraints, this challenge aims to develop AI models that deliver consistent diagnostic performance across diverse camera environments. Through the Multi-Camera Robust Diagnosis of Fundus Diseases (MuCaRD) challenge, we will evaluate both robust classification algorithms that generalize to unseen devices and adaptive learning techniques that can quickly fine-tune using only a few sample images from a new camera.

Challenge Description

Overview:
The MuCaRD challenge addresses a critical gap in AI‐driven fundus screening: ensuring consistent performance across both familiar and unseen camera systems. Participants will develop and benchmark models under realistic constraints—training on a limited set of images from one device and then evaluating robustness and adaptability on entirely new devices. By simulating clinical and commercial deployment scenarios, MuCaRD promotes methods that generalize beyond a single data source and can quickly fine‐tune to novel imaging hardware.

Tasks:

Task 1: Zero-Shot Classification
Train on fundus images from a single camera and evaluate on completely unseen devices. Participants perform two separate binary classifiers (glaucoma vs. normal, and referable DR vs. non-referable), submitting full model code and weights to the CodaLab platform. A hidden validation set (200 images each from Optomed Aurora, Mediworks FC162, Optos Ultra Wide, Canon CR2) and a similarly‐sized test set ensure no data leakage.
Task 2: Few-Shot Test-Time Adaptation
Extend Task 1 by leveraging a small support set (5 labeled images per new camera: 1 positive, 4 negative) provided online during validation and test phases. Models should demonstrate on-the-fly adaptation within a 10 s/image inference limit, showcasing both robustness and efficient fine-tuning.

Datasets:

AI-READI dataset: A rigorously curated set of high-resolution color fundus images acquired on Optomed Aurora and Eidon cameras across three Bridge2AI partner sites (UAB, UCSD, UW). Images span all four type 2 diabetes severity categories and include expert-verified annotations for diabetic retinopathy stage, image quality scores, and linked clinical metadata (age, sex, HbA1c, blood pressure, comorbidities). This cohort is optimized to benchmark zero-shot model performance and cross-device generalization.
Mediwhale Collection: Training from one CR2 and testing images from 5 different cameras.

Evaluation & Metrics:
Performance is measured by the average of the Area Under the ROC Curve (AUROC) and the Area Under the Precision–Recall Curve (AUPRC) for each disease. To mirror clinical feasibility, all inference and adaptation steps must complete within 10 seconds per image, though this limit does not directly penalize the score. Submissions are limited to two runs per day during validation to curtail leaderboard overfitting.

Important Dates

Training Release: June 30, 2025
Validation Submission: June 30 – August 15, 2025
Test Submission: August 15 – August 23, 2025
Winner Announcement: August 30, 2025
Workshop: October 6–10, 2025

Awards
Certificates will be presented to the top three teams in each task.
The first and corresponding authors of the winning teams will be invited to co-author the challenge summary paper and to present their results at the workshop.

Contact
For inquiries, please email: g.young@mediwhale.com

B2AI Discussion Forum on Emerging ELSI Issues: “The Pulse of Ethical Machine Learning in Health” by Marzyeh Ghassemi, Ph.D.
2025-07-15 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, July 15th, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum:
“The Pulse of Ethical Machine Learning in Health“, by Dr. Marzyeh Ghassemi
Registration not required!
Additional details in the attached documents and message below.
Bio:
Dr. Marzyeh Ghassemi is an Associate Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES). She holds MIT affiliations with the Jameel Clinic, LIDS, IDSS, and CSAIL. For examples of short- and long-form talks Professor Ghassemi has given, see her Forbes lightning talk, and her ICML keynote.
Professor Ghassemi holds a Germeshausen Career Development Professorship, and was named a CIFAR Azrieli Global Scholar and one of MIT Tech Review’s 35 Innovators Under 35. In 2024, she received an NSF CAREER award, and Google Research Scholar Award. Prior to her PhD in Computer Science at MIT, she received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar, and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University.
Professor Ghassemi’s work spans computer science and clinical venues, including NeurIPS, KDD, AAAI, MLHC, JAMIA, JMIR, JMLR, AMIA-CRI, Nature Medicine, Nature Translational Psychiatry, and Critical Care. Her work has been featured in popular press such as MIT News, The Boston Globe, and The Huffington Post.

Cell Maps for AI (CM4AI) CodeFest at University of Alabama Birmingham
2025-08-14 08:00 - 2025-08-15 17:00 (America/Los_Angeles) | University of Alabama at Birmingham
Are you interested in AI/ML and their applications in biomedicine and precision healthcare? Join the Functional Genomics Grand Challenge team and their group of interdisciplinary experts for the 2025 Cell Maps for AI (CM4AI) CodeFest at UAB.
This two-day, in-person event is a hands-on workshop centered on the development of team-based projects using CM4AI datasets and state-of-the-art AI/ML tools to design and test novel approaches in cancer research, drug discovery, systems biology, and precision medicine. Teams will present their projects virtually, with cash awards available for the top 3!
To register, please visit the link here.
Registration Deadline: August 6th, 2025
For questions, please contact: cm4ai@yale.edu
CodeFest Themes
Participants will collaborate in teams to build and present projects that leverage CM4AI data and tools, with guidance from mentors at UAB, Yale, UCSD, and other CM4AI institutions.
Focus areas include:

Biomedical graph networks
Graph & quantum AI/ML methods
Data embedding
Data visualization
Visible neural networks
Large language models

B2AI Discussion Forum on Emerging ELSI Issues: “Data Management in the Extremes” by Dr. Jennifer Wagner
2025-08-19 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, August 19th, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Data Management in the Extremes”, by Dr. Jennifer Wagner.
Registration not required!
Additional details in the attached documents and message below.
Bio:
Jennifer K. Wagner, JD, PhD, is an Assistant Professor at Penn State University, affiliated with law, engineering, anthropology, and biomedical sciences. A licensed attorney since 2007, her interdisciplinary research focuses on the human right to science, privacy, and equity in genetic and digital health technologies. She has published over 70 articles, received NIH funding, and her work has been cited by the U.S. Supreme Court. She serves on editorial boards and national ethics committees and teaches courses on genetics law, privacy, and biomedical AI.

B2AI Discussion Forum on Emerging ELSI Issues: “Rational Health AI and Respect for Persons” by Dr. Ida Sim
2025-09-16 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, September 16th, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Relational Health AI and Respect for Persons”, by Dr. Ida Sim
Registration not required!
Additional details in the attached documents and message below.
Bio:
Ida Sim, MD, PhD is Professor of Medicine (UCSF) and Computational Precision Health (UCSF and UC Berkeley) and Co-Director of the UCSF UC Berkeley Joint Program in Computational Precision Health. She obtained her B.Sc. in Biology, her MD, and her PhD in Medical Informatics from Stanford. A practicing primary care physician, Dr. Sim completed her Internal Medicine internship and residency at the Massachusetts General Hospital and a fellowship in General Medicine at the Palo Alto VA.

Dr. Sim’s research is on cyberinfrastructure and policies for large-scale health data sharing and AI for managing multiple chronic conditions in primary care. She is Co-founder of Open mHealth, which defines the IEEE 1752 global open standard for patient-generated health data interoperability, and co-leads JupyterHealth, a new project bringing the Jupyter ecosystem to healthcare. She is also Co-founder of Vivli, the world’s largest platform for clinical trial data sharing. In prior work, Dr. Sim was the founding Project Coordinator of the World Health Organization’s International Clinical Trials Registry Platform and led the establishment of the first global policy on clinical trial registration.

Dr. Sim is a member of the National Academy of Medicine and the American Society for Clinical Investigation, a Fellow of the American College of Medical Informatics, and a recipient of the United States Presidential Early Career Award for Scientists and Engineers (PECASE).

B2AI Discussion Forum on Emerging ELSI Issues: “The Observer Project: Transforming Healthcare from the Outside” by Dr. Kevin Johnson
2025-10-21 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, October 21st, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “The Observer Project: Transforming Healthcare from the Outside”, by Dr. Kevin Johnson.
Registration not required!
Additional details in the attached documents and message below.
Bio:
Kevin B. Johnson, MD, MS is the David L. Cohen University Professor of Biomedical Informatics, Computer Science, Pediatrics, and Science Communication at the University of Pennsylvania, and Vice President of Applied Clinical Informatics in the University of Pennsylvania Health System. He received his MD from Johns Hopkins and his MS in Medical Informatics from Stanford University. Previously, he served as Chair for the Department of Biomedical Informatics and Chief Informatics Officer for Vanderbilt University Medical Center.

A clinical informatics researcher, Johnson was among the world’s first researchers to propose and demonstrate the value of text-messaging in behavior change. Dr. Johnson developed the first ever computer-based documentation system used at Hopkins, as well as the first e-prescribing system used at Vanderbilt—both of which became platforms for numerous evaluations by Johnson and his trainees. As director of the Penn Artificial Intelligence for Ambulatory Care Innovation (AI4AI), he and his lab focus on various uses of AI to reimagine the clinical encounter.

He has authored over 200 publications and has won numerous national awards. He was elected to the American College of Medical Informatics in 2004 (FACMI) and (FAMIA), The Academic Pediatric Society in 2010, the National Academy of Medicine in 2010, the International Association of Health Science Informatics in 2021 (FIAHSI), the American Institute of Medical and Biological Engineering in 2022 (FAIMBE).

TRM LLM Module Lecture: "Spatial Intelligence: A Key to Embodied AI" with Parisa Kordjamshidi
2025-12-11 12:00 - 13:00 (America/Los_Angeles)
Join us on Thursday, December 11, 2025, at 12:00 PM PT/3:00 PM ET for the lecture: “Spatial Intelligence: A Key to Embodied AI” with Parisa Kordjamshidi, PhD. This will be the 5th installment in the Bridge2AI Training, Recruitment, and Mentoring (TRM) 2025-26 Lecture Series Large Language Model (LLM) Module.
Learning Objectives:

Define spatial reasoning and generalization within the context of AI model development.
Identify and explain the current limitations of large vision–language models.
Describe neurosymbolic AI modeling and articulate how it can enhance model generalization

Biography:
Dr. Parisa Kordjamshidi is an Associate Professor of Computer Science and Engineering at Michigan State University since 2019. After her PhD (KU Leuven, Belgium), she completed her postdoctoral training at the KnowEng Center of NIH BD2K Program at UIUC. At MSU, her research spans Artificial Intelligence (AI), machine learning, natural language processing (NLP), neuro-symbolic AI, and multi-modal LLMs. She currently directs the Heterogeneous Learning & Reasoning Lab at MSU. She is the recipient of the NSF CAREER Award (2019–24), the Amazon Faculty Research Award (2022), and the Fulbright Scholar Award (2025).
Dr. Kordjamshidi has a strong publication record across leading AI and NLP venues, including ACL, EMNLP, NAACL, NeurIPS, AAAI, IJCAI, and ICLR. She serves as the Action Editor of TACL and as a member of the editorial boards of JAIR and other impactful journals. She has served on organizing committees for major conferences such as NAACL, EMNLP, ECML-PKDD, and AAAI, and as a (senior) area chair or program committee member for top venues including ACL, IJCAI, NAACL, EMNLP, and AAAI.

TRM LLM Module Lecture: “Navigating Ethical AI in Healthcare: Protecting Consumers and Patients” with Adela Grand
2025-12-18 12:00 - 13:00 (America/Los_Angeles)
Join us on Thursday, December 18, 2025, at 12:00 PM PT/3:00 PM ET for the lecture: “Navigating Ethical AI in Healthcare: Protecting Consumers and Patients” with Adela Grand, PhD. This will be the 6th installment in the Bridge2AI Training, Recruitment, and Mentoring (TRM) 2025-26 Lecture Series Large Language Model (LLM) Module.
Learning Objectives:

Explain why ethical principles are essential in the design and evaluation of AI-based mental health applications.
Identify and critique key components of the FUTURE-AI framework for ensuring trustworthy and human-centered AI systems.
Apply the FUTURE-AI framework to evaluate an AI-based mental mobile app for robustness.

Biography:
Dr. Adela Grando, PhD, FAMIA, FACMI, is a Professor of Biomedical Informatics at Arizona State University and an Adjunct Assistant Professor at the Mayo Clinic. At ASU, her research focuses on healthcare information technology, patient-centered technologies, and mobile health, with an emphasis on privacy-preserving data sharing and clinical decision support. She completed postdoctoral training at UCSD’s Division of Biomedical Informatics and at Oxford and Edinburgh Universities through UK Cancer Research, following her PhD training in Spain.
Dr. Grando has an extensive publication record in leading venues, including AI in Medicine, the Int. J. of Med. Inform., and Applied Clin. Inform. She previously served as Associate Editor for the Health Informatics Journal and currently serves on the editorial boards of the Journal of Biomedical Informatics and AI in Medicine. She is recognized as a Fellow of both the American Medical Informatics Association (FAMIA) and the American College of Medical Informatics (FACMI).

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Trust Starts Upstream: Recommendations for Creating Ethically Sourced Health Data Repositories for AI/ML"
2026-01-20 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, January 20th, 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Trust Starts Upstream: Recommendations for creating ethically sourced health data repositories for AI/ML,” by Dr. Camille Nebeker.

Creating ethically sourced and trustworthy health data repositories is critical for building trustworthy biomedical and behavioral research infrastructure, especially when such repositories underpin machine learning and AI systems. In Ethical sourcing in the context of health data supply chain management: a value sensitive design approach (Nebeker et al., 2025), we integrate value sensitive design (VSD) with concepts from supply chain management to operationalize ethical values across the stages of developing health data repositories. The resulting framework identifies key actors, values (e.g., traceability, security, equity), and tensions that arise during repository creation and highlights practices such as documenting data provenance, articulating expectations for data stewards, and implementing comprehensive privacy and bias mitigation strategies.
During this session, Dr. Nebeker will provide an overview of this framework with a focus on developing a companion checklist that is grounded in VSD and supply chain scaffolding and can be used as actionable guidance in dataset creation.

Bio:
Dr. Camille Nebeker is a professor of public health with appointments in the UC San Diego Design Lab and the Herbert Wertheim School of Public Health and Human Longevity Science. In 2018, Dr. Nebeker co-founded the ReCODE Health center, which is dedicated to conducting cutting edge research to inform ethical practices in digital/AI health research – including machine learning and the use of large language models. The ReCODE Health center supports education and consultation services to guide ethical practices in technology-supported health research across diverse research sectors including traditional academic research and, increasingly, the health technology sector. She’s a principal investigator with the Bridge2AI Bridge Center’s Ethical, Legal and Social Implications Core.

TRM Novel AI Technology Module Lecture: "Beyond LLMs: Neuro-Symbolic Approaches for Language Understanding in the Biomedical Domain" by Dr. Mihai Surdeanu
2026-01-29 15:00 - 16:00 (America/New_York)
“Join us on Thursday, January 29, 2026, at 12:00 PM PT/3:00 PM ET for the lecture: “Beyond LLMs: Neuro-Symbolic Approaches for Language Understanding in the Biomedical Domain” by Dr. Mihai Surdeanu. This lecture is part of the Bridge2AI Training, Recruitment, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module.
Lecture Learning Objectives:

Understand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.
Learn how to build symbolic and neuro-symbolic natural language processing systems that are faithful, pliable, and fast.

Biography:
Dr. Mihai Surdeanu is a Professor of Computer Science in the College of Science at the University of Arizona, with joint appointments in Linguistics and Cognitive Science. His research focuses on natural language processing, including question answering, information extraction, and building systems that derive meaning from unstructured text, with a strong emphasis on interpretable models that can explain their decisions.
Dr. Surdeanu has received the ACL Outstanding Area Chair Award (2023) and the Distinguished Scholar Award from the University of Arizona’s Department of Computer Science (2023). He is an active contributor to the NLP community, serving as an Action Editor for Transactions of the Association for Computational Linguistics (TACL) since 2019 and as Senior Area Chair for ACL (2023, 2025) and EMNLP (2022). He has held Area Chair roles for EMNLP, NAACL, and COLING–LREC across multiple years. Dr. Surdeanu has also served on program committees for ACL and EMNLP for a long time, in addition to contributing to COLM, COLING, as well as Graph-Based NLP and Pan-DL workshops.”
Introduction Slides

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Pragmatic and Nimble AI Governance in Healthcare"
2026-02-17 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, February 17th 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Pragmatic and Nimble AI Governance in Healthcare“, by Dr. Susannah Rose.

Dr. Susannah Rose will discuss the ethical issues related deploying system-wide artificial intelligence in healthcare delivery organizations. This presentation will focus on the practical governance policies, process and challenges. Attendees will have the opportunity to ask questions as part of an engaging and dynamic presentation.

Bio:

Dr. Rose is an ethicist and mixed-methods researcher specializing in patient experience and the ethics of artificial intelligence (AI) in healthcare. She is an Associate Professor at Vanderbilt University Medical Center and serves as Vice-Chair of VUMC’s AI Technology Committee and Executive Director of the ADVANCE Center. Dr. Rose previously founded the AI + Ethics Program at Cleveland Clinic, teaches public health ethics at Harvard T.H. Chan, and her research is funded by organizations including ARPA-H, NIH, and The Greenwall Foundation.

TRM Novel AI Technology Module Lecture: "Encrypted Machine Learning" by Dr. Vishnu Boddeti
2026-02-19 15:00 - 16:00 (America/New_York)
Join us on Thursday, February 19, 2026, at 12:00 PM PT/3:00 PM ET for the lecture: “Encrypted Machine Learning” by Dr. Vishnu Boddeti. This lecture is part of the Bridge2AI Training, Recruitment, and Mentoring (TRM) 2025-26 Lecture Series Novel AI Technology Module.
Lecture Learning Objectives:

Understand the advantages and disadvantages of neural (in particular LLM) architectures vs. neuro-symbolic approaches in the biomedical space.
Learn how to build symbolic and neuro-symbolic natural language processing systems that are faithful, pliable, and fast.

Biography:
Dr. Vishnu Boddeti is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University and the Director of the Human Analysis Lab. His research focuses on developing AI systems with provable guarantees of fairness, privacy, and accuracy, with applications spanning high-stakes scientific and societal domains. His work includes auditing and mitigating bias in foundation models through fairness–utility trade-offs and adversarial red-teaming, designing cryptographically secure AI systems using homomorphic encryption and FHE-native architectures, and advancing physics-informed AI for scientific discovery by integrating physical laws to improve generalization and reduce data requirements.
He has received multiple distinguished research honors, including the 2024 IEEE-CCF Cloud Computing Best Paper Award, Best Paper Awards at IROS 2023 and IEEE TBIOM (2022–2023), and recognition as an Editor Highlight in Nature Communications. He is also a recipient of a Facebook Research Grant on Multi-objective Co-evolutionary Learning (2021). Dr. Boddeti is an active contributor to the research community, serving as Senior Area Editor for IEEE Transactions on Information Forensics and Security (2025) and Area Chair for NeurIPS (2025) and AutoML (2023). His research demonstrates that well-designed cryptographic, statistical, and physical constraints can enable AI capabilities, providing both theoretical foundations and practical systems for trustworthy AI deployment in scientific and biomedical contexts.”
Introduction

Bridge2AI Discussion Forum on Emerging ELSI Issues: “Conjoint analysis of perspectives on ethical tradeoffs in data generation project"
2026-03-17 15:00 - 16:00 (America/New_York)
Please join us on Tuesday, March 17th 2026 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “Conjoint analysis of perspectives on ethical tradeoffs in data generation project”, by Dr. Dr. Nicholas G. Evans.
Registration not required!, view past recordings here.
Additional details in the attached documents and message below.
Bio:
Dr. Nicholas G. Evans, Ph.D. is Associate Professor of Political Science at the University of Massachusetts Lowell, where he co-directs the Modelling Individual and Networked Decisions (MIND) Lab. His work focuses on the intersection of ethics, infectious disease, emerging technologies, and national security. His current major projects focus on ethics of artificial intelligence, funded by the National Institutes of Health, US Army Research Laboratory DEVCOM, and Greenwall Foundation.
Dr. Evans is best known for his work on “dual-use research of concern,” beneficial scientific research that has a risk of misuse in the development of weapons of mass destruction. In 2012 he completed one of the first Ph.D. dissertations on the ethics of dual-use research of concern, where he wrote on the scope and strength of scientific freedom in the face of national security concerns. He has since published more than a dozen articles, books, and book chapters on dual-use research. In Spring 2025 he published Gain of Function with The MIT Press Essential Knowledge Series, providing a thoroughgoing guide to the topic, its controversies, and future.
Dr. Evans is also a recognized expert in public health ethics, writing on the ethics of social distancing, research ethics during health emergencies, and the use of force in pandemic response. His 2016 collection, Ebola’s Message: Public Health and Medicine in the 21st Century received favorable reviews in Nature from Dr. Peter Piot, who first identified the virus in 1976. His new book on the ethics of pandemic preparedness and response, War on All Fronts: A Theory of Health Security Justice, was published in May 2023. Both are available open access at The MIT Press Website.
Prior to his appointment at the University of Massachusetts Lowell, Dr. Evans completed postdoctoral research at the University of Pennsylvania. In 2015, he held an Emerging Leaders in Biosecurity Initiative Fellowship at the UPMC Center for Health Security, Baltimore; has held visiting appointments at the Universities of Exeter, Bradford, and Cambridge; and is a three-time Fondation Brocher resident scholar in bioethics in Hermance, Switzerland. He is also a former policy officer with the Australian Department of Health where he worked on therapeutics regulation, and assisted reproduction policy.

2026 Voice AI Symposium & Hackathon
2026-05-04 - 2026-05-06 | The Vinoy Resort & Golf Club, 501 5th Ave NE, St. Petersburg, FL, 33701, United States
Registration and Call for Science are now open for the 2026 Bridge2AI Voice Symposium + Hackathon! Join us May 4–6, 2026, in beautiful St. Petersburg, Florida, for one of the only global events dedicated entirely to voice biomarkers.
The Voice AI Symposium has become an internationally-recognized event and one of the only conferences focused solely on the research, development, and implementation of voice biomarkers to improve healthcare. Unlike some large-scale tech conferences, the Voice AI Symposium is intentionally intimate and designed to give every attendee meaningful opportunities to meet pioneers, tastemakers, and thought leaders shaping the future of healthcare through voice AI technologies. Building on the success of past years, the 2026 Voice AI Symposium will bring together the forefront innovators, researchers, clinicians, entrepreneurs, and industry leaders of the voice biomarker space for a two-day immersive experience at the forefront of voice and AI in healthcare.

Highlights will include:

Hands-on Training & Workshops using the Bridge2AI-Voice dataset and tools.
Podium presentations selected through an open Call for Science
Interactive Panels & Keynotes featuring international experts and visionaries in healthcare and AI.
Tech Fair & Demos where attendees can experience cutting-edge applications of voice AI.
Pitch Competition spotlighting groundbreaking startups.
Networking Events designed to foster real connections across disciplines.
and more!

Submit your most innovative research and technology under this year’s theme:
“Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare.”
Key Dates:
Abstract Submission Deadline: December 5, 2025
Notification of Selection: January 15, 2026
Symposium + Hackathon: May 4–6, 2026
Don’t miss your chance to be part of this global movement at the intersection of voice, data, and health innovation — and to connect with the community shaping the next era of healthcare AI.
Register early to secure your spot — there is limited capacity!
Voice AI Symposium: https://www.eventsquid.com/event.cfm?id=29517
Call for Science: https://www.eventsquid.com/event.cfm?id=30025
